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Top Up Credits with Crypto

top_up

Simulated crypto top-up for a QuantifyMe DEV server only: no money moves, so it never makes an account paid and grants at most up to the free credit cap ($100 per call). quantifyme.ai refuses it (#1098) and answers with how to pay for real: send USDC on Base to your deposit address (GET /api/v1/wallet/deposit_address). Returns your new credit balance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amount_usdYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=false, openWorldHint=true and idempotentHint=false; the description adds the substantive behavior an agent needs: no real money moves, the account never becomes paid, grants are capped at the $100 free credit cap per call, and it returns the new credit balance. This is exactly the kind of side-effect and limit disclosure annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The DEV-only scoping constraint is front-loaded and nearly every clause carries new information (no money, cap, refusal code, alternative endpoint, return value). It is dense but not padded; the parenthetical endpoint is the only clause that could arguably be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter mutation tool with an output schema already covering the return shape, the description still supplies the dev-only constraint, the credit cap, the production failure mode and the real-payment alternative. Nothing an agent needs in order to decide whether and how to call it is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the single parameter amount_usd has no description, so the description must compensate. It partially does by revealing the $100-per-call cap that bounds the value, but it never states the unit/format or behavior when the amount exceeds the cap, leaving the only parameter under-specified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Simulated crypto top-up' granting credits) and immediately scopes it to 'a QuantifyMe DEV server only,' which no sibling tool covers. An agent can tell at a glance that this is not a real payment tool and not one of the strategy/model tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-not: 'quantifyme.ai refuses it (#1098)' on production, plus the alternative path for real payment ('send USDC on Base to your deposit address (GET /api/v1/wallet/deposit_address)'). Both the exclusion and the substitute action are named, so the agent does not have to infer routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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